Prediction of bitterness based on modular designed graph neural network.

Motivation: Bitterness plays a pivotal role in our ability to identify and evade harmful substances in food. As one of the five tastes, it constitutes a critical component of our sensory experiences. However, the reliance on human tasting for discerning flavors presents cost challenges, rendering in silico prediction of bitterness a more practical alternative. Results: In this study, we introduce the use of Graph Neural Networks (GNNs) in bitterness prediction, superseding traditional machine learning techniques. We developed an advanced model, a Hybrid Graph Neural Network (HGNN), surpassing conventional GNNs according to tests on public datasets. Using HGNN and three other GNNs, we designed BitterGNNs, a bitterness predictor that achieved an AUC value of 0.87 in both external bitter/non-bitter and bitter/sweet evaluations, outperforming the acclaimed RDKFP-MLP predictor with AUC values of 0.86 and 0.85. We further created a bitterness prediction website and database, TastePD (https://www.tastepd.com/). The BitterGNNs predictor, built on GNNs, offers accurate bitterness predictions, enhancing the efficacy of bitterness prediction, aiding advanced food testing methodology development, and deepening our understanding of bitterness origins. Availability and implementation: TastePD can be available at https://www.tastepd.com, all codes are at https://github.com/heyigacu/BitterGNN.

Dual-polarization RF channelizer based on microcombs.

We report a dual-polarization radio frequency (RF) channelizer based on microcombs. Two high-Q micro-ring resonators (MRRs) with slightly different free spectral ranges (FSRs) are used: one MRR is pumped to yield soliton crystal microcombs ("active"), and the other MRR is used as a "passive" periodic optical filter supporting dual-polarization operation to slice the RF spectrum. With the tailored mismatch between the FSRs of the active and passive MRRs, wideband RF spectra can be channelized into multiple segments featuring digital-compatible bandwidths via the Vernier effect. Due to the use of dual-polarization states, the number of channelized spectral segments, and thus the RF instantaneous bandwidth (with a certain spectral resolution), can be doubled. In our experiments, we used 20 microcomb lines with ∼ 49 GHz FSR to achieve 20 channels for each polarization, with high RF spectra slicing resolutions at 144 MHz (TE) and 163 MHz (TM), respectively; achieving an instantaneous RF operation bandwidth of 3.1 GHz (TE) and 2.2 GHz (TM). Our approach paves the path towards monolithically integrated photonic RF receivers (the key components - active and passive MRRs are all fabricated on the same platform) with reduced complexity, size, and unprecedented performance, which is important for wide RF applications with digital-compatible signal detection.

Synthesis of Indolyl Phenyl Diketones through Visible-Light-Promoted Ni-Catalyzed Intramolecular Cyclization/Oxidation Sequence of Ynones.

The combination of visible light catalysis and Ni catalysis has enabled the synthesis of indolyl phenyl diketones through the cyclization/oxidation process of ynones. This reaction proceeded under mild and base-free conditions and showed a broad scope and feasibility for gram-scale synthesis. Several natural products and biologically interesting molecules could be readily postfunctionalized by this method.

Mulberry Leaf Compounds and Gut Microbiota in Alzheimer's Disease and Diabetes: A Study Using Network Pharmacology, Molecular Dynamics Simulation, and Cellular Assays.

Recently, studies have reported a correlation that individuals with diabetes show an increased risk of developing Alzheimer's disease (AD). Mulberry leaves, serving as both a traditional medicinal herb and a food source, exhibit significant hypoglycemic and antioxidative properties. The flavonoid compounds in mulberry leaf offer therapeutic effects for relieving diabetic symptoms and providing neuroprotection. However, the mechanisms of this effect have not been fully elucidated. This investigation aimed to investigate the combined effects of specific mulberry leaf flavonoids (kaempferol, quercetin, rhamnocitrin, tetramethoxyluteolin, and norartocarpetin) on both type 2 diabetes mellitus (T2DM) and AD. Additionally, the role of the gut microbiota in these two diseases' treatment was studied. Using network pharmacology, we investigated the potential mechanisms of flavonoids in mulberry leaves, combined with gut microbiota, in combating AD and T2DM. In addition, we identified protein tyrosine phosphatase 1B (PTP1B) as a key target for kaempferol in these two diseases. Molecular docking and molecular dynamics simulations showed that kaempferol has the potential to inhibit PTP1B for indirect treatment of AD, which was proven by measuring the IC50 of kaempferol (279.23 µM). The cell experiment also confirmed the dose-dependent effect of kaempferol on the phosphorylation of total cellular protein in HepG2 cells. This research supports the concept of food-medicine homology and broadens the range of medical treatments for diabetes and AD, highlighting the prospect of integrating traditional herbal remedies with modern medical research.

Correlation Between Blood Cadmium Levels and Platelet Characteristics, As Well As Their Impact on Susceptibility to Coronary Heart Disease: Findings from NHANES 2005-2018 Data.

Investigating the correlation between blood cadmium levels, platelet characteristics, and susceptibility to coronary heart disease (CHD). Utilized NHANES 2005-2018 data with covariates such as age, sex, race, marital status, and socio-economic status. Blood cadmium served as the independent variable, while platelet count (PC) and mean platelet volume (MPV) were dependent variables. The average age of the participants was 68.77 ± 11.03 years, and 67.4% of them were male. The mean values for WBC, MPV, PC, and blood cadmium were 7.53 ± 3.36 × 103 cells/µL, 11.33 ± 0.27fL, 57.61 ± 5.34 × 103 cells/µL, and 2.58 ± 0.61 µg/L, respectively. Adjusting for other variables revealed increased MPV and PC with rising blood cadmium levels in cardiac patients, indicating a higher risk of CHD in those with elevated blood cadmium. The average age of the participants was 68.77 ± 11.03 years, and 67.4% of them were male. The mean values for WBC, MPV, PC, and blood cadmium were 7.53 ± 3.36 × 103 cells/µL, 11.33 ± 0.27fL, 57.61 ± 5.34 × 103 cells/µL, and 2.58 ± 0.61 µg/L, respectively. Adjusting for other variables revealed increased MPV and PC with rising blood cadmium levels in cardiac patients, indicating a higher risk of CHD in those with elevated blood cadmium. This study enhances understanding of how cadmium impacts platelet characteristics, contributing to increased CHD risk, providing insights for primary prevention strategies.

Mlp4green: A Binary Classification Approach Specifically for Green Odor.

Fresh green leaves give off a smell known as "green odor." It has antibacterial qualities and can be used to attract or repel insects. However, a common method for evaluating green odor molecules has never existed. Machine learning techniques are widely used in research to forecast molecular attributes for binary classification. In this work, the green odor molecules were first trained and learned using machine learning methods, and then clustering analysis and molecular docking were performed to further explore their molecular characteristics and mechanisms of action. For comparison, four algorithmic models were employed, MLP performed the best in all metrics, including Accuracy, Precision, Average Precision, Matthews coefficient, and Area under curve. We determined by difference analysis that, in comparison to non-green odor molecules, green odor molecules have a lower molecular mass and fewer electrons. Based on the MLP algorithm, we constructed a binary classification prediction website for green odors. The first application of deep learning techniques to the study of green odor molecules can be seen as a signal of a new era in which green odor research has advanced into intelligence and standardization.

Novel design and development of Centella Asiatica extract - loaded poloxamer/ZnO nanocomposite wound closure material to improve anti-bacterial action and enhanced wound healing efficacy in diabetic foot ulcer.

Diabetic wounds can occur as a prevalent complication among people diagnosed with diabetes, frequently resulting in the necessity for amputation. The cause and effect of diabetic foot ulcer is complex, involving multiple factors. In the present study, wound healing strategies utilizing nanomaterials have proven to be effective in battling bacterial infections and improve wound regeneration. Poloxamers (PLX) exhibit extensive potential as a viable option for the development of nanomedicines owing to their inherent characteristics of self-assembly and encapsulation. This study aims to design and develop a PLX/ZnO nanocomposite incorporated with Centella Asiatica extract (CAE) for the multi-functional action in the diabetic wound healing treatment. Subsequently physico-chemical characterizations, such as XRD, FTIR, and TEM observations, demonstrated that the ZnO were evenly distributed through the PLX framework. The developed nanocomposite was biocompatible with mouse fibroblast cell line (L929), and it had multiple beneficial characteristics, such as a rapid self-healing process and effective antibacterial action against G+ and G- bacterial pathogens. After being treated with the developed formulation, skin fibroblast cell line and HUVECs demonstrated a substantial increase in their in vitro cell proliferation ability, migration, and tube-forming abilities. The utilization of a CAE@PLX/ZnO nanoformulation presents a viable strategy and a distinctive, encouraging composite for diabetic wound healing treatment.

Exploring the anti-gout potential of sunflower receptacles alkaloids: A computational and pharmacological analysis.

Gout, a painful condition marked by elevated uric acid levels often linked to the diet's high purine and alcohol content, finds a potential treatment target in xanthine oxidase (XO), a crucial enzyme for uric acid production. This study explores the therapeutic properties of alkaloids extracted from sunflower (Helianthus annuus L.) receptacles against gout. By leveraging computational chemistry and introducing a novel R-based clustering algorithm, "TriDimensional Hierarchical Fingerprint Clustering with Tanimoto Representative Selection (3DHFC-TRS)," we assessed 231 alkaloid molecules from sunflower receptacles. Our clustering analysis pinpointed six alkaloids with significant gout-targeting potential, particularly emphasizing the fifth cluster's XO inhibition capabilities. Through molecular docking and the BatchDTA prediction model, we identified three top compounds-2-naphthylalanine, medroxalol, and fenspiride-with the highest XO affinity. Further molecular dynamics simulations assessed their enzyme active site interactions and binding free energies, employing MM-PBSA calculations. This investigation not only highlights the discovery of promising compounds within sunflower receptacle alkaloids via LC-MS but also introduces medroxalol as a novel gout treatment candidate, showcasing the synergy of computational techniques and LC-MS in drug discovery.

Effects of dietary supplementation of fish oil plus vitamin D3 on gut microbiota and fecal metabolites, and their correlation with nonalcoholic fatty liver disease risk factors: a randomized controlled trial.

We previously reported that fish oil plus vitamin D3 (FO + D) could ameliorate nonalcoholic fatty liver disease (NAFLD). However, it is unclear whether the beneficial effects of FO + D on NAFLD are associated with gut microbiota and fecal metabolites. In this study, we investigated the effects of dietary supplementation of FO + D on gut microbiota and fecal metabolites and their correlation with NAFLD risk factors. Methods: A total of 61 subjects were randomly divided into three groups: FO + D group (2.34 g day-1 of eicosatetraenoic acid (EPA) + docosahexaenoic acid (DHA) + 1680 IU vitamin D3), FO group (2.34 g day-1 of EPA + DHA), and corn oil (CO) group (1.70 g d-1 linoleic acid). Blood and fecal samples were collected at the baseline and day 90. Gut microbiota were analyzed through 16S rRNA PCR analysis, and fecal co-metabolites were determined via untargeted ultraperformance liquid chromatography-quadrupole time-of-flight mass spectrometry (UPLC-Q-TOF-MS). Results: The relative abundance of Eubacterium (p = 0.03) and Lactobacillus (p = 0.05) increased, whereas that of Streptococcus (p = 0.02) and Dialister (p = 0.04) decreased in the FO + D group compared with the CO group. Besides, changes in tetracosahexaenoic acid (THA, C24:6 n-3) (p = 0.03) levels were significantly enhanced, whereas 8,9-DiHETrE levels (p < 0.05) were reduced in the FO + D group compared with the CO group. The changes in 1,25-dihydroxyvitamin D3 levels in the fecal samples were inversely associated with insulin resistance, which was determined using the homeostatic model assessment model (HOMA-IR, r = -0.29, p = 0.02), and changes in 8,9-DiHETrE levels were positively associated with adiponectin levels (r = -0.43, p < 0.05). Conclusion: The present results indicate that the beneficial effects of FO + D on NAFLD may be partially attributed to the impact on gut microbiota and fecal metabolites.

Sigmoido-rectal intussusception anastomosis in the Altemeier procedure for complete rectal prolapse: preliminary results of a new technique.

Purpose: Our research introduces an innovative surgical approach, combining the Altemeier Procedure with Sigmoido-rectal Intussusception Anastomosis, effectively reducing recurrence, minimizing complications, and improving postoperative anal function in rectal prolapse patients. Materials and methods: This retrospective study, conducted at tertiary referral hospitals including Shandong University of Traditional Chinese Medicine's Affiliated Hospital, Linyi People's Hospital, and Pingyi People's Hospital, examined data from patients undergoing conventional Altemeier surgery or Altemeier combined with Sigmoido-rectal Intussusception Anastomosis. Analyzing hospitalization and follow-up data from January 2009 to December 2022, the study focused on prolapse recurrence, complications, and anal function as primary outcome indicators across these three study centers. Results: In the study, both groups had an average follow-up of (12.5 ± 2.41) months, and only two traditional group patients experienced mortality. Recurrence rates significantly differed, with 26.47% in the traditional group and 1.54% in the modified group (P < 0.001). The modified group showed no perioperative anastomotic dehiscence, contrasting with a 13.24% occurrence in the conventional group (P = 0.003). Primary complications in the modified group included anastomotic hemorrhage, with rates of 17.65% and 6.15% in the traditional and modified groups, respectively (P = 0.077). At 12 months postoperatively, both groups improved in anal manometry parameters and the Wexner anal incontinence score. Resting pressure was significantly lower in the traditional group (32.50 ± 1.76 mmHg) than the modified group (33.24 ± 2.06 mmHg) (P = 0.027), while the extrusion pressure was higher in the modified group (64.78 ± 1.55 mmHg) than the traditional group (62.85 ± 2.30 mmHg) (P < 0.001). The Wexner anal incontinence score was significantly lower in the modified group (2.69 ± 1.65) than the traditional group (3.69 ± 1.58, P = 0.001). Conclusion: This retrospective study affirms that adding Sigmoido-rectal Intussusception Anastomosis to the Altemeier procedure reduces recurrence and complications. While both approaches enhance postoperative anal function in complete rectal prolapse patients, the combined method, particularly with Sigmoido-rectal Intussusception Anastomosis, proves more effective.

Building a Kokumi Database and Machine Learning-Based Prediction: A Systematic Computational Study on Kokumi Analysis.

Kokumi is a subtle sensation characterized by a sense of fullness, continuity, and thickness. Traditional methods of taste discovery and analysis, including those of kokumi, have been labor-intensive and costly, thus necessitating the emergence of computational methods as critical strategies in molecular taste analysis and prediction. In this study, we undertook a comprehensive analysis, prediction, and screening of the kokumi compounds. We categorized 285 kokumi compounds from a previously unreleased kokumi database into five groups based on their molecular characteristics. Moreover, we predicted kokumi/non-kokumi and multi-flavor compositions using six structure-taste relationship models: MLP-E3FP, MLP-PLIF, MLP-RDKFP, SVM-RDKFP, RF-RDKFP, and WeaveGNN feature of Atoms and Bonds. These six predictors exhibited diverse performance levels across two different models. For kokumi/non-kokumi prediction, the WeaveGNN model showed an exceptional predictive AUC value (0.94), outperforming the other models (0.87, 0.90, 0.89, 0.92, and 0.78). For multi-flavor prediction, the MLP-E3FP model demonstrated a higher predictive AUC and MCC value (0.94 and 0.74) than the others (0.73 and 0.33; 0.92 and 0.70; 0.95 and 0.73; 0.94 and 0.64; and 0.88 and 0.69). This data highlights the model's proficiency in accurately predicting kokumi molecules. As a result, we sourced kokumi active compounds through a high-throughput screening of over 100 million molecules, further refined by toxicity and similarity screening. Lastly, we launched a web platform, KokumiPD (https://www.kokumipd.com/), offering a comprehensive kokumi database and online prediction services for users.

Using deep learning and molecular dynamics simulations to unravel the regulation mechanism of peptides as noncompetitive inhibitor of xanthine oxidase.

Xanthine oxidase (XO) is a crucial enzyme in the development of hyperuricemia and gout. This study focuses on LWM and ALPM, two food-derived inhibitors of XO. We used molecular docking to obtain three systems and then conducted 200 ns molecular dynamics simulations for the Apo, LWM, and ALPM systems. The results reveal a stronger binding affinity of the LWM peptide to XO, potentially due to increased hydrogen bond formation. Notable changes were observed in the XO tunnel upon inhibitor binding, particularly with LWM, which showed a thinner, longer, and more twisted configuration compared to ALPM. The study highlights the importance of residue F914 in the allosteric pathway. Methodologically, we utilized the perturbed response scan (PRS) based on Python, enhancing tools for MD analysis. These findings deepen our understanding of food-derived anti-XO inhibitors and could inform the development of food-based therapeutics for reducing uric acid levels with minimal side effects.

Fluorescence color change of supramolecular polymer networks controlled by crown ether-cation recognition.

We report a fluorescent supramolecular polymer networks (SPNs) system based on crown ether-cation recognition. The polymer side chains bear ammonium cations, which can be recognized by host molecules with a B15C5 unit and a quinoline group at each end. The quinoline group makes the host molecule exhibit blue fluorescence. After the formation of SPNs, the recognition of the crown ether-cation transforms the blue fluorescence into yellow fluorescence. The accompanying fluorescence color change during the formation of SPNs makes it with potential applications in the fields of display, printing, information storage, and bioimaging.

Network Pharmacology Combined with Machine Learning to Reveal the Action Mechanism of Licochalcone Intervention in Liver Cancer.

There are reports indicating that licochalcones can inhibit the proliferation, migration, and invasion of cancer cells by promoting the expression of autophagy-related proteins, inhibiting the expression of cell cycle proteins and angiogenic factors, and regulating autophagy and apoptosis. This study aims to reveal the potential mechanisms of licochalcone A (LCA), licochalcone B (LCB), licochalcone C (LCC), licochalcone D (LCD), licochalcone E (LCE), licochalcone F (LCF), and licochalcone G (LCG) inhibition in liver cancer through computer-aided screening strategies. By using machine learning clustering analysis to search for other structurally similar components in licorice, quantitative calculations were conducted to collect the structural commonalities of these components related to liver cancer and to identify key residues involved in the interactions between small molecules and key target proteins. Our research results show that the seven licochalcones molecules interfere with the cancer signaling pathway via the NF-κB signaling pathway, PDL1 expression and PD1 checkpoint pathway in cancer, and others. Glypallichalcone, Echinatin, and 3,4,3',4'-Tetrahydroxy-2-methoxychalcone in licorice also have similar structures to the seven licochalcones, which may indicate their similar effects. We also identified the key residues (including ASN364, GLY365, TRP366, and TYR485) involved in the interactions between ten flavonoids and the key target protein (nitric oxide synthase 2). In summary, we provide valuable insights into the molecular mechanisms of the anticancer effects of licorice flavonoids, providing new ideas for the design of small molecules for liver cancer drugs.

Advancing the fitness of gut commensal bacteria.

Nutrient starvation of beneficial bacteria helps them colonize the human gut.

Probing the mechanisms of hydrazide-based HDAC inhibitors binding to HDAC3 using Gaussian accelerated molecular dynamics (GaMD) simulations.

Histone deacetylases (HDACs) have emerged as promising targets for anticancer drug development. They regulate gene expression by removing acetyl groups from lysine residues on histone tails, leading to chromatin condensation. A hydrazide-based HDAC inhibitor, N-(4-(2-Propylhydrazine-1-carbonyl)benzyl)-1H-indole-2-carboxamide (11h), has been reported to exhibit significant in vivo antitumor activity. In comparison to the lead compound N-(4-(2-Propylhydrazine-1-carbonyl)benzyl)cinnamamide (17), compound 11h demonstrates 2- to 5-fold higher HDAC inhibition and cell-based antitumor activity. However, the inhibitory mechanism of 11h remains insufficiently explored. In this study, we conducted 500 ns Gaussian Accelerated Molecular Dynamics (GaMD) simulations on Histone deacetylase 3 (HDAC3) and two complex systems (HDAC3-17 and HDAC3-11h). Our findings revealed that upon inhibitor binding, the active pocket volume of HDAC3 undergone alterations, and the movement of the L6-loop toward the active site impeded substrate entry. Moreover, we observed a destabilization of the α-helix in the aa75-89 region of HDAC3 compared to the two complex systems, indicating partial unwinding. Notably, 11h exhibited a closer proximity of its carbonyl oxygen to the active pocket's Zn2+ metal compared to 17, increasing the likelihood of coordination with the Zn2+ metal. The analysis of protein-ligand interactions highlighted a greater number of hydrogen bonds and other interactions between 11h and the receptor protein when compared to 17, underscoring the stronger binding of 11h to HDAC3. In conclusion, our study provided theoretical insights into the inhibitory mechanism of hydrazide-based HDAC inhibitors on HDAC3, thereby contributing to the development of improved drug targets for cancer therapy.Communicated by Ramaswamy H. Sarma.

Functionalized Fullerene Potentially Inhibits SARS-CoV-2 Infection by Modulating Spike Protein Conformational Changes.

The disease of SARS-CoV-2 has caused considerable morbidity and mortality globally. Spike proteins on the surface of SARS-CoV-2 allow it to bind with human cells, leading to infection. Fullerenes and their derivatives are promising SARS-CoV-2 inhibitors and drug-delivery vehicles. In this study, Gaussian accelerated molecular dynamics simulations and the Markov state model were employed to delve into the inhibitory mechanism of Fullerene-linear-polyglycerol-b-amine sulfate (F-LGPS) on spike proteins. During the study, it was discovered that fullerene derivatives can operate at the interface of the receptor-binding domain (RBD) and the N-terminal domain (NTD), keeping structural domains in a downward conformation. It was also observed that F-LGPS demonstrated superior inhibitory effects on the XBB variant in comparison to the wild-type variant. This study yielded invaluable insights for the potential development of efficient therapeutics targeting the spike protein of SARS-CoV-2.

Investigating the Vital Role of the Identified Abietic Acid from Helianthus annuus L. Calathide Extract against Hyperuricemia via Human Embryonic Kidney 293T Cell Model.

To explore the anti-hyperuricemia components in sunflower (Helianthus annuus L.) calathide extract (SCE), we identified abietic acid (AA) via liquid chromatography-mass spectrometry and found an excellent inhibitor of xanthine oxidase (IC50 = 10.60 µM, Ki = 193.65 nM) without cytotoxicity. Based on the transcriptomics analysis of the human embryonic kidney 293T cell model established using 1 mM uric acid, we evaluated that AA showed opposite modulation of purine metabolism to the UA group and markedly suppressed the intensity of purine nucleoside phosphorylase, ribose phosphate pyrophosphokinase 2, and ribose 5-phosphate isomerase A. Molecular docking also reveals the inhibition of purine nucleoside phosphorylase and ribose phosphate pyrophosphokinase 1. The SCE exhibits similar regulation of these genes, so we conclude that AA was a promising component in SCE against hyperuricemia. This present study provided a novel cell model for screening anti-hyperuricemia natural drugs in vitro and illustrated that AA, a natural diterpenoid, is a potential inhibitor of purine biosynthesis or metabolism.

F-Doped Carbon Nanoparticles-Based Nucleation Assistance for Fast and Uniform Three-Dimensional Zn Deposition.

Aqueous Zn metal-based batteries have considerable potential as energy storage system; however, their application is extremely limited by dendrite development and poor reversibility. In this study, to overcome both challenges, F-doped carbon nanoparticles (FCNPs) are uniformly constructed on substrates (Ti, Zn, Cu, and steel) by a plasma-assisted surface modification, which endows reversible and uniform deposition of Zn metal. FCNPs with high surface charge density act as nucleation assistors and form numerous homogenous Zn nucleation sites toward Zn 3D growth, which improves Zn plating kinetic and results in uniform Zn deposition. Furthermore, the ZnF2  solid electrolyte interface generated during cycling contributes to rapid mass transfer and enhances Zn reversibility, but also suppresses the side reaction. Accordingly, the half-cell of P-Ti coupled with Zn exhibits an average Coulombic efficiency of 99.47% with 500 cycles. The symmetric cell of the P-Zn anode presents a lifespan of over 1500 h at the current density of 5 mA cm-2 . Notably, the cell works for 100 h at 50 mA cm-2 . It is believed that this ingenious surface modification broadens revolutionary methods for uniform metallic deposition, as well as the dendrite-free rechargeable batteries system.